HDF5 file format

Data storage in academia and research & development

The huge number of data formats and various import and export options can make data handling in research a challenging and time-consuming task. To tackle this challenge and make your life easier, after many hours spent on research on data storage, we found the Hierarchical Data Format 5 (HDF5) to be the best format to cover all major requirements for our automation framework thaTEC:OS. Furthermore, it is already a standard format and widely used in industrial and academic research.

Consequently, we are changing the data format of our software framework thaTEC:OS to HDF5 and you can directly profit from this update in your daily work and with respect to good scientific practice:

  1. Performance and flexibility: HDF5 offers high-speed data acquisition with no restrictions on file size, handles complex data types, and can be extended by new data sets at any time. Raw data including meta data, lab book, and evaluation results: our measurement files will adapt to your needs and as our framework evolves.
  2. Accessibility and workflow: HDF5 is a self-describing data format that does not require additional documentation to be interpreted by a wide range of cross-platform open-source and commercial tools like HDF View and Origin or via the programming interfaces to all major languages including Python, Matlab, and LabVIEW: directly read and write our measurement files with the tools of your choice and transparently share them with your colleagues!
  3. Long-term archiving solution: The mission of the TheHDFGroup is to ensure long-term availability of HDF technologies and long-term accessibility of data stored using HDF technologies. This active maintenance and the large number of tools and programming interfaces to interprete the data format are the ideal basis for an long-term archiving solution.

Check out our new version of thaTEC:OS and the corresponding LabVIEW examples and Python scripts to access our measurement files.

Table of contents